writing-great-skills

Design, review, and refactor AI skills for deterministic execution.

7|Updated Apr 10, 2026
One-click install
npx skills add https://github.com/carl10086/ys-powers --skill writing-great-skills-carl10086
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: writing-great-skills
Source: https://github.com/carl10086/ys-powers/tree/main/skills/writing-great-skills
Command: npx skills add https://github.com/carl10086/ys-powers --skill writing-great-skills-carl10086

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This skill addresses the inconsistency and unpredictability often found in AI-driven workflows by providing a structured methodology for designing, refining, and maintaining high-quality skills and commands.

Core Features & Use Cases

  • Predictability Framework: Establishes clear guidelines for model-invoked vs. user-invoked triggers to optimize context usage.
  • Information Hierarchy: Provides a systematic approach to organizing steps and references to prevent premature completion and cognitive overload.
  • Use Case: Use this skill when you are drafting a new automation for your team and need to ensure the AI follows a deterministic process, or when you need to prune an existing, bloated skill to improve its reliability.

Quick Start

Use the writing-great-skills skill to review my current draft for a new automation and suggest improvements based on the predictability framework.

Frequently Asked Questions about writing-great-skills

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I make AI prompt engineering workflows more predictable?

You can ensure deterministic AI execution by applying a predictability framework that establishes clear guidelines for model-invoked triggers, information hierarchy, and progressive disclosure to prevent premature completion and cognitive overload.

What is the best way to structure prompts for complex workflow automation?

The best way to structure complex workflow automation is to implement an information hierarchy that organizes steps and references systematically, preventing cognitive overload and ensuring the AI follows a deterministic process.

How do I refactor a bloated AI agent skill to improve reliability?

Refactor a bloated AI agent skill by applying a structured methodology to prune existing commands, enforce a single source of truth, and optimize context usage through progressive disclosure, which directly improves execution reliability.

Does this methodology work for both user-invoked and model-invoked agent triggers?

Yes, the methodology applies to both user-invoked and model-invoked agent triggers by establishing clear guidelines to optimize context usage and ensure predictable execution across different command-line tools and custom capabilities.

Why does my AI agent stop or complete tasks prematurely during workflow automation?

AI agents complete tasks prematurely due to poor information hierarchy and lack of progressive disclosure. Organizing steps and references systematically prevents this issue and ensures the workflow runs to completion deterministically.